The COVID pandemic seems to have raised the question, ‘whether existing supply chain (SC) disruption philosophies and strategies continue to remain valid?’. This article assesses the differences in the business scenarios pre-and post-COVID. The authors capture the mathematical and operational relationships amongst the relevant factors and propose a System Dynamics (SD) model to carry out the simulations. The approach considers the impact of the force majeure condition, that is, COVID period on individuals’ income, prices and demand of goods, cost of input and supply of finished goods. The results show that earnings may increase demand but, disruption in supplies of raw materials and finished products nullify the effect. On the other hand, even if flow returns to normal, reduced income affects normal goods businesses. JEL Codes: R41

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The challenges presented by recent changes in the business environment have sharpened the focus on the need for robust approaches to supply chain improvement. For most companies around the world, resources have been reduced, inventory drained, technology spending curtailed, and core processes scaled back in order to adjust to the current reality of reduced demand. So, this paper mainly concentrates on giving some tips based on recession recovery strategies. Firstly, this paper discussed the supply chain management trends in and up to 2015, then general concept of recession and the relation between recession and supply chain management system, then some fatal mistakes of recession recovery according to the supply chain experts and recession and recovery related literature reviews are summarized to identify ultimately the recession recovery strategies for the manufacturer. The paper ended with some supply chain management related predictions, tips for reducing supply chain barriers. Moreover, a brief section of this paper also here highlights the supply-chain infrastructure helpful for recession recovery that is one of the important factors for the reason of cost-reduction, resource planning and maintenance etc. in today's supply chain management and related environment.

Supply chains today are, primarily, measured by Key Performance Indicators (KPIs) such as order-fulfillment, availability to the consumer (percent in-stock) and cost reduction, as well as financial KPIs such as return on investment (ROI), return on brand equity and inventory. These KPIs measure the performance of supply chain as a whole. A supply chain is a network of nodes. The performances of individual nodes are measured with KPIs such as production rate, shipment rate, inventory and the like. These metrics may indicate the performance but may not indicate the cause of such performance. For example, a node whose production rate is below the desired level may be because of poor supply of inputs of production by its supplier node.Thus mere identification of KPIs and their evaluation will not enable to identify the root cause of a problem in a supply chain. Therefore, we need a business intelligence framework that will satisfy the objectives, namely, identification of outcome of each node of the supply chain and its cause. The existing Supply Chain Intelligence (SCI) frameworks aims at identifying metrics that reflect the performance of individual nodes and the total supply chain, but fail to identify the cause of such outcomes. It implies that the linkages or association between the KPIs of individual nodes are required to be identified and defined. In this paper, contingency and systems approach has been used to identify the dimensions of the firm, its internal environment, the complement and the external environment. A system dynamics based approach has been used to identify the causality and resulting behavior of the supply chain. The paper proposes a SCI framework and a System dynamics Model that help in identifying the reasons for supply chin performance and lead to the actions required to be taken for improvement in performance of the supply chain.